Application of SQSTM1 in preparation of liver cell carcinoma prognosis evaluation and immunotherapy target drug

Abstract

The application discloses application of SQSTM1 in preparation of a hepatocellular carcinoma prognosis evaluation and immunotherapy target drug, and relates to the biomedical technical field; a kit for evaluating prognosis of a hepatocellular carcinoma patient, wherein the kit comprises nucleic acid primers and probes capable of specifically detecting SQSTM1 mRNA; and the nucleic acid primers and probes are used for real-time fluorescent quantitative PCR detection or high-throughput sequencing. The application proves that high expression of SQSTM1 mRNA is an independent risk factor for shortening of total survival time of a HCC patient through integration of multiple large independent queue data such as TCGA, ICGC and GEO, and the prognosis judging value is verified in different data sets; and a reliable molecular index is provided for the clinic, which can be used for more accurate prognosis risk stratification of the HCC patient and assisting in formulating an individualized treatment scheme.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the application of SQSTM1 in the preparation of drugs for hepatocellular carcinoma prognostic assessment and immunotherapy. Background Technology

[0002] Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, ranging from simple hepatic steatosis to nonalcoholic steatohepatitis (NASH), which can progress to hepatocellular carcinoma (HCC). With a deeper understanding of ferroptosis, its therapeutic potential in cancer has been proposed, but it has not yet translated into effective treatments. LONP1, FADS2, and SQSTM1, as regulators of ferroptosis, may play important roles in tumorigenesis and development. LONP1 is associated with tumor invasion, metastasis, and proliferation; FADS2 affects cellular sensitivity to ferroptosis; and SQSTM1 is involved in the pathogenesis and progression of various metabolic diseases.

[0003] This invention aims to analyze the cell type-specific expression of LONP1 and FADS2 in the liver using single-cell RNA sequencing technology, and to evaluate their prognostic value, methylation regulation mechanism, and association with the tumor immune microenvironment in HCC using TCGA, ICGC, and GEO databases. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing the application of SQSTM1 in the preparation of hepatocellular carcinoma prognostic assessment and immunotherapy target drugs.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A kit for assessing the prognosis of patients with hepatocellular carcinoma, the kit comprising nucleic acid primers and probes capable of specifically detecting SQSTM1 mRNA; the nucleic acid primers and probes are used for real-time quantitative PCR detection or high-throughput sequencing.

[0006] A kit for assessing the prognosis of patients with hepatocellular carcinoma (HCC) includes an antibody or antigen-binding fragment thereof capable of specifically binding to the SQSTM1 protein; the kit is used for immunohistochemical detection or Western blot detection; the kit further includes a standard curve for quantifying the SQSTM1 detection signal into expression level data, and reference values ​​for judging HCC prognosis based on SQSTM1 expression levels.

[0007] A prognostic assessment system for hepatocellular carcinoma includes: The sample detection unit is used to receive biological samples from HCC patients and output SQSTM1 expression level data. The data processing unit has a pre-stored prognostic assessment model, which is based on the risk association between SQSTM1 expression level and patient overall survival, and the association between SQSTM1 expression level and the infiltration level of regulatory T cells and memory B cells in the tumor immune microenvironment. The data processing unit is configured to: receive SQSTM1 expression level data from the sample detection unit, call the prognostic assessment model to perform calculations, and output an assessment report containing prognostic risk level and immune microenvironment characteristics.

[0008] Preferably, the sample detection unit is one of a qPCR instrument, a sequencer, an immunohistochemical scanning analyzer, or a Western blot imaging analyzer.

[0009] Application of reagents for detecting the SQSTM1 gene or its expression product in the preparation of products for the adjuvant assessment of prognosis in patients with hepatocellular carcinoma.

[0010] Preferably, the auxiliary assessment includes comparing the patient's SQSTM1 expression level with a reference value for judging HCC prognosis based on SQSTM1 expression level, thereby providing clinicians with prognostic risk information.

[0011] A method for screening candidate drugs for the treatment of hepatocellular carcinoma includes the following steps: S1: Provides a testing system for expressing SQSTM1; S2: Bring the candidate material into contact with the test system; S3: Detect changes in at least one of the following indicators in the test system: Indicator 1: Expression level or activity of SQSTM1; Indicator 2: Expression levels of immune checkpoint molecules TNFSF9, TNFSF18, CD40, or CD44 that are associated with SQSTM1 function; Indicator 3: The activity or proportion of regulatory T cells in the test system; S4: Select candidate substances that can lower indicator 1, and / or lower indicator 2, and / or reduce indicator 3.

[0012] Preferably, the test system is an HCC cell line expressing SQSTM1, an HCC organoid, or an HCC animal model.

[0013] A pharmaceutical composition for treating hepatocellular carcinoma comprises an siRNA molecule capable of downregulating SQSTM1 gene expression, the sequence of said siRNA targeting the coding region or 3'UTR region of human SQSTM1 mRNA; the pharmaceutical composition further comprises a pharmaceutically acceptable carrier and is intended for use in combination with drugs targeting immune checkpoints TNFSF9, TNFSF18, CD40, or CD44.

[0014] Preferably, the pharmaceutical composition further comprises a pharmaceutically acceptable carrier and is intended for use in combination with a drug that targets immune checkpoints TNFSF9, TNFSF18, CD40, or CD44.

[0015] The beneficial effects of this invention are as follows: 1. This invention, by integrating multiple large independent cohort datasets such as TCGA, ICGC, and GEO, systematically confirms that high expression of SQSTM1 mRNA is an independent risk factor for shortened overall survival in HCC patients, and its prognostic value has been validated in different datasets; it provides a reliable molecular indicator for clinical use, which can be used to perform more precise prognostic risk stratification of HCC patients and assist in the development of individualized treatment plans.

[0016] 2. This invention found that the expression of SQSTM1 is significantly associated with specific remodeling of the immune microenvironment in HCC tumors; high expression of SQSTM1 is positively correlated with increased infiltration of immunosuppressive cells and upregulation of the expression of multiple immune checkpoint molecules; SQSTM1 is not only a prognostic marker, but also a potential therapeutic target that can act on both tumor cells themselves and the immune system, providing a direction for developing novel therapies aimed at reversing the immunosuppressive microenvironment.

[0017] 3. This invention combines the expression level of SQSTM1 with its regulatory information on the immune microenvironment; the prognostic assessment system or model constructed based on this can not only predict survival outcomes, but also simultaneously indicate the immune microenvironment characteristics of the patient's tumor, providing additional information for predicting the patient's potential response to existing immune checkpoint inhibitor therapies, and is more practical.

[0018] 4. This invention clarifies that SQSTM1 is a key node in regulating the immune microenvironment of HCC; targeting SQSTM1 can both directly inhibit tumor cells and reshape the immune microenvironment. Attached Figure Description

[0019] Figure 1 This is a single-cell transcriptome diagram of the liver of a healthy human subject according to the present invention; Figure 2 This is a functional enrichment map of hepatocytes with high FADS2 expression according to the present invention; Figure 3 This is a functional enrichment map of hepatocytes with high LONP1 expression according to the present invention; Figure 4 This is a schematic diagram illustrating the prognostic value and diagnostic ROC of LONP1, FADS2, and SQSTM1 in this invention. Figure 5 This is a methylation analysis diagram of the LONP1 and FADS2 promoters in this invention; Figure 6 This is a schematic diagram illustrating the correlation between LONP1 and immune cell infiltration in this invention. Figure 7 This is a schematic diagram illustrating the correlation between the SQSTM1 of this invention and immune cell infiltration. Figure 8 This is a schematic diagram illustrating the correlation between LONP1 and SQSTM1 and immune checkpoints in this invention. Detailed Implementation

[0020] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0021] Example 1: Regulation of LONP1 and FADS2 in HCC prognosis and immune microenvironment 1. Single-cell data preprocessing and cell type identification: Single-cell transcriptome datasets (GSE115469 and GSE124395) were collected from healthy donor liver tissue. Data processing was performed using the R package Seurat, and batch effects were eliminated using the FindIntegrationAnchors and IntegrateData functions. Cell types were annotated according to literature and the CellMarker website. Data visualization was performed using UMAP and ggplot2.

[0022] 2. Enrichment analysis: Differentially identified genes in single-cell data were annotated using the DAVID database and subjected to GO annotation and KEGG pathway enrichment analysis. A p-value < 0.05 was considered statistically significant. Bubble plots were generated using the R package ggplot2.

[0023] 3. Data Acquisition and Processing (HCC Section): Gene expression profiles and corresponding clinical information from TCGA and GTEx were downloaded from the UCSCXena database. Gene expression data were converted to TPM, and log2(TPM+0.01) was used in the analysis. The impact of relevant gene expression on overall survival in HCC patients was further validated in the ICGC datasets (LIRI-JP and LIHC-US projects). The GSE14520 and GSE76427 microarray datasets were extracted from the GEO database.

[0024] 4. Prognostic analysis: The impact of FADS2, LONP1, and SQSTM1 on the survival of HCC patients was assessed using the TCGA, ICGC, and GEO databases, and Kaplan-Meier survival curves were plotted. ROC analysis was used to evaluate the diagnostic value.

[0025] 5. Gene methylation analysis: The relative methylation levels (β values) of promoters of ferroptosis regulators in HCC and normal liver tissues were retrieved from the UALCAN database and analyzed. The correlation between promoter methylation levels and relative expression of target genes was assessed and plotted using the ChAMP and ggplot2R packages.

[0026] 6. Immune cell infiltration analysis: Tumor tissues were divided into two groups based on the expression levels of LONP1 or SQSTM1. The relative abundance of tumor-infiltrating lymphocytes in the low- and high-expression groups was assessed using CIBERSORT. The Spearman test was used to further analyze the correlation between LONP1 or SQSTM1 and tumor invasion. The correlation between the expression levels of 46 common immune checkpoint genes and the expression levels of LONP1 and SQSTM1 was investigated.

[0027] 7. Statistical analysis methods: Statistical analysis was performed using R software, and a p-value or corrected p-value ≤ 0.05 was considered statistically significant.

[0028] result 1: Single-cell transcriptomics reveals that LONP1 and FADS2 are specifically expressed in hepatocytes. scRNA-seq analysis of normal human liver tissue revealed that cells were divided into 17 populations ( Figure 1 AB), based on marker gene annotation of cell type ( Figure 1 C). FADS2 and LONP1 are mainly expressed in hepatocytes, while SQSTM1 is expressed in almost all cell types. Figure 1 DE). Extraction of hepatocyte clusters ( Figure 1 F), grouped according to the median expression of FADS2 (F) Figure 1 G).

[0029] Caption ( Figure 1AG): Single-cell transcriptome atlas of healthy human liver. (A) UMAP dimensionality reduction plot after integrating two single-cell datasets (GSE115469 and GSE124395), colored by dataset. (B) UMAP plot showing 17 cell populations. (C) Cell types based on marker gene annotation, including hepatocytes, T cells, NK cells, Kupffer cells, endothelial cells, etc. (DE) Feature maps showing the expression distribution of FADS2 (D) and LONP1 (E) in each cell population, with darker colors indicating higher expression. (F) Re-clustering UMAP plot of hepatocyte subsets. (G) Hepatocytes divided into high (red) and low (blue) expression groups based on median FADS2 expression.

[0030] Conclusion: FADS2 and LONP1 exhibit high cell type specificity in the liver and are mainly expressed in hepatocytes, providing a cellular-level localization basis for subsequent functional studies.

[0031] 2: Hepatocytes with high FADS2 expression are significantly enriched in fatty acid metabolism-related pathways. GO and KEGG analyses showed that the FADS2 high expression group was enriched in fatty acid β-oxidation, PPAR signaling pathway, etc. Figure 2 AB).

[0032] Caption ( Figure 2 (A) Functional enrichment of hepatocytes with high FADS2 expression. (B) GO enrichment bubble plot of differentially expressed genes in the high vs. low FADS2 expression groups, showing significant enrichment in fatty acid β-oxidation, lipid metabolism, etc. (C) KEGG enrichment bubble plot, showing significant enrichment in the PPAR signaling pathway, fatty acid degradation, TCA cycle, etc.

[0033] Conclusion: Hepatocytes with high FADS2 expression are in an active state of fatty acid catabolism and energy metabolism, suggesting that FADS2 may participate in the progression of NAFLD by regulating lipid metabolism.

[0034] 3: LONP1-overexpressing hepatocytes are enriched in the glycolysis / gluconeogenesis pathway. The same analysis was performed on LONP1, and GO was enriched in fatty acid β-oxidation, while KEGG was enriched in glycolysis / gluconeogenesis. Figure 3 AC).

[0035] Caption ( Figure 3 AC): Functional enrichment of hepatocytes with high LONP1 expression. (A) Hepatocytes were grouped according to the median LONP1 expression. (B) GO enrichment bubble plot of differentially expressed genes in the high vs. low LONP1 expression groups, showing significant enrichment in fatty acid β-oxidation. (C) KEGG enrichment bubble plot, showing significant enrichment in glycolysis / gluconeogenesis and metabolic pathways.

[0036] Conclusion: Hepatocytes with high LONP1 expression are involved in both fatty acid oxidation and glucose metabolism reprogramming, suggesting that LONP1 plays multiple roles in the regulation of energy metabolism in hepatocytes.

[0037] 4: High expression of LONP1 and FADS2 is significantly associated with poor prognosis in HCC patients. Survival analysis showed that in TCGA ( Figure 4 A), ICGC-LIRI-JP ( Figure 4 B) and GEO ( Figure 4 In database D), high expression of FADS2, LONP1, and SQSTM1 all led to poor prognosis in HCC patients; in the ICGC-LIRI-US database, high expression of LONP1 and SQSTM1 led to poor prognosis, while FADS2 had no significant effect. Figure 4 C). ROC analysis showed that the AUC of both LONP1 and SQSTM1 was greater than 0.7 ( Figure 4 E).

[0038] Caption ( Figure 4 (A) Prognostic value and diagnostic ROC of LONP1, FADS2, and SQSTM1 in the TCGA-LIHC cohort. (B) Survival curves (Log-rank test) for high expression (red) and low expression (blue) groups. (C) Survival curves for the ICGC-LIRI-JP cohort. (D) Survival curves for the GEO cohort (GSE14520). (E) ROC curves of LONP1 and SQSTM1 in diagnosing HCC in the TCGA dataset, with AUC values ​​of 0.81 and 0.76, respectively.

[0039] Conclusion: High expression of LONP1 and FADS2 is a significant risk factor for poor prognosis in HCC patients. Among them, LONP1 has shown robustness in multiple independent cohorts and has potential prognostic value.

[0040] 5: The expression of LONP1 and FADS2 is dynamically regulated by promoter methylation. LONP1 methylation levels showed no significant difference between HCC and normal tissues. Figure 5 A). However, in HCC tissues, LONP1 expression is negatively correlated with methylation levels ( Figure 5 B), especially the sites cg13451483 (R=-0.16, p=0.0045) and cg03595538 (R=-0.23, p=7.5e-05). Figure 5 C). FADS2 expression is negatively correlated with promoter methylation ( Figure 5D), cg06781209 (R=-0.37, p=5.6e-11) and cg21709803 (R=-0.35, p=1e-09) showed the highest negative correlation. Figure 5 E). SQSTM1 promoter methylation levels are lower in HCC than in normal liver tissue (E). Figure 5 A), but expression was not significantly correlated with methylation level.

[0041] Caption ( Figure 5 (A) Comparison of LONP1, FADS2, and SQSTM1 promoter methylation β values ​​between HCC and normal liver tissue in the UALCAN database (*p<0.05). (B) Scatter plot showing the negative correlation between LONP1 mRNA expression and its overall promoter methylation level (Spearman test). (C) Scatter plot showing the negative correlation between LONP1 expression and the methylation levels at cg13451483 and cg03595538 sites. (D) Negative correlation between FADS2 expression and its overall promoter methylation level. (E) Scatter plot showing the negative correlation between FADS2 expression and the methylation levels at cg06781209 and cg21709803 sites.

[0042] Conclusion: The expression of LONP1 and FADS2 is negatively regulated by methylation at specific CpG sites in the promoter. Although the FADS2 promoter is hypermethylated overall, its upregulation may be related to hypomethylation at specific sites.

[0043] 6: LONP1 expression is significantly associated with HCC immune microenvironment remodeling. TCGA-LIHC cohort analysis showed that, compared with the low LONP1 expression group, the high LONP1 expression group had higher levels of infiltration of resting dendritic cells and resting CD4+ memory T cells, while the infiltration levels of resting NK cells and plasma cells were lower. Figure 6 A). LONP1 mRNA levels were negatively correlated with infiltration of resting dendritic cells and resting CD4+ memory T cells, and positively correlated with infiltration of resting NK cells and plasma cells. Figure 6 B).

[0044] Caption ( Figure 6 (A) Correlation between LONP1 and immune cell infiltration. (B) CIBERSORT analysis showed the difference in the abundance of 22 immune cell infiltration between the high and low expression groups of LONP1 (*p<0.05). (C) Heatmap showing the Spearman correlation coefficient between LONP1 expression and the level of infiltration of various immune cells.

[0045] Conclusion: High expression of LONP1 is associated with the infiltration characteristics of immunosuppressive cells in HCC, suggesting that LONP1 may be involved in shaping the immunosuppressive microenvironment.

[0046] 7: SQSTM1 expression is also significantly associated with immune cell infiltration. The SQSTM1 high expression group showed higher infiltration levels of resting CD4+ memory T cells, γδ T cells, and Tregs, while the infiltration levels of memory B cells, monocytes, neutrophils, resting NK cells, and plasma cells were lower. Figure 7 A). SQSTM1 mRNA levels were negatively correlated with infiltration of resting CD4+ memory T cells and Tregs, and positively correlated with infiltration of monocytes, resting NK cells, and plasma cells. Figure 7 B).

[0047] Caption ( Figure 7 (A) Correlation between SQSTM1 and immune cell infiltration. (B) Heatmap showing the correlation between SQSTM1 expression and immune cell infiltration.

[0048] Conclusion: The expression of SQSTM1 is also significantly associated with the infiltration level of various immune cells in HCC, but its mode of action is different from that of LONP1.

[0049] 8: LONP1 and SQSTM1 are positively correlated with multiple immune checkpoint molecules. No correlation was found between FADS2 and immune cell infiltration. Immune checkpoint analysis showed that LONP1 expression was positively correlated with CD276, TNFRSF4, TNFRSF14, and TNFRSF18. Figure 8 B); SQSTM1 expression was positively correlated with TNFSF9, TNFSF18, CD40, and CD44. Figure 8 C).

[0050] Caption ( Figure 8 AC): Correlation between LONP1 and SQSTM1 and immune checkpoints. (A) Heatmap of the correlation between the expression of 46 immune checkpoint genes and LONP1 and SQSTM1. (B) Scatter plot of the correlation between representative immune checkpoints (CD276, TNFRSF4, etc.) and LONP1 expression. (C) Scatter plot of the correlation between representative immune checkpoints (TNFSF9, CD40, etc.) and SQSTM1 expression.

[0051] Conclusion: The expression of LONP1 and SQSTM1 was significantly positively correlated with multiple immune checkpoint molecules, suggesting they may be potential targets for HCC immunotherapy. No significant association was found between FADS2 and immune infiltration or immune checkpoints in this study.

[0052] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A kit for assessing the prognosis of patients with hepatocellular carcinoma, characterized in that, The kit contains nucleic acid primers and probes that can specifically detect SQSTM1 mRNA; the nucleic acid primers and probes are used for real-time quantitative PCR detection or high-throughput sequencing.

2. A kit for assessing the prognosis of patients with hepatocellular carcinoma, characterized in that, The kit contains an antibody or its antigen-binding fragment that specifically binds to the SQSTM1 protein; the kit is used for immunohistochemical detection or Western blot detection; the kit also contains a standard curve for quantifying the SQSTM1 detection signal into expression level data, and reference values ​​for judging the prognosis of HCC based on the SQSTM1 expression level.

3. A prognostic assessment system for hepatocellular carcinoma, characterized in that, include: The sample detection unit is used to receive biological samples from HCC patients and output SQSTM1 expression level data. The data processing unit has a pre-stored prognostic assessment model, which is based on the risk association between SQSTM1 expression level and patient overall survival, and the association between SQSTM1 expression level and the infiltration level of regulatory T cells and memory B cells in the tumor immune microenvironment. The data processing unit is configured to: receive SQSTM1 expression level data from the sample detection unit, call the prognostic assessment model to perform calculations, and output an assessment report containing prognostic risk level and immune microenvironment characteristics.

4. The system according to claim 3, characterized in that, The sample detection unit is one of a qPCR instrument, a sequencer, an immunohistochemical scanning analyzer, or a Western blot imaging analyzer.

5. Application of reagents for detecting the SQSTM1 gene or its expression product in the preparation of products for assisting in the prognosis assessment of patients with hepatocellular carcinoma.

6. The application according to claim 5, characterized in that, The auxiliary assessment includes comparing the patient's SQSTM1 expression level with a reference value for judging HCC prognosis based on SQSTM1 expression level, thereby providing clinicians with prognostic risk information.

7. A method for screening candidate drugs for the treatment of hepatocellular carcinoma, characterized in that, Includes the following steps: S1: Provides a testing system for expressing SQSTM1; S2: Bring the candidate material into contact with the test system; S3: Detect changes in at least one of the following indicators in the test system: Indicator 1: Expression level or activity of SQSTM1; Indicator 2: Expression levels of immune checkpoint molecules TNFSF9, TNFSF18, CD40, or CD44 that are associated with SQSTM1 function; Indicator 3: The activity or proportion of regulatory T cells in the test system; S4: Select candidate substances that can lower indicator 1, and / or lower indicator 2, and / or reduce indicator 3.

8. The method according to claim 7, characterized in that, The test system is an HCC cell line expressing SQSTM1, an HCC organoid, or an HCC animal model.

9. A pharmaceutical composition for treating hepatocellular carcinoma, characterized in that, The pharmaceutical composition contains an siRNA molecule capable of downregulating SQSTM1 gene expression, the sequence of which targets the coding region or 3'UTR region of human SQSTM1 mRNA; the pharmaceutical composition further comprises a pharmaceutically acceptable carrier and is intended for use in combination with drugs that target immune checkpoints TNFSF9, TNFSF18, CD40, or CD44.

10. The pharmaceutical composition according to claim 9, characterized in that, The pharmaceutical composition further comprises a pharmaceutically acceptable carrier and is intended for use in combination with drugs that target immune checkpoints TNFSF9, TNFSF18, CD40, or CD44.

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